• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.510-514
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• 1994

This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.158-161
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• 1995

A new laser diode range-finding speedometer is proposed, which is modulated by a pair of positive and negative triangular pulse current superimposed on a dc current. Since a target velocity is directly obtained form a pure Doppler beat frequency measured during the non-modulation period, the new sensor is free from the difficulties due to the critical velocity encountered in the previous sensor. Furthermore, the different amplitude of the two triangular pluses are so adjusted that the measurable range using only one laser head is greatly expanded to 10cm through 150cm, which is about two times that of the previous sensor. The measurement accuracy for velocity of .+-.6mm/s through .+-.20mm/s and for range is about 1%, and 2%, respectively. Because the new sensor can be operated automatically using a microcomputer, it will be useful for application of a 3-D range image measurement of a slowly moving object.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.232-237
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• 2010

In this paper, a slit light laser range finding method using perspective warping calibration is proposed. This approach has an advantage to acquire relatively high accuracy, although the optical system is nonlinear. In the calibration, we detect the calibration points which are marked on the calibration panel and acquire the center position of the slit light laser in the image, which are used for computing the real positions of the slit light by using perspective warping. A calibration file is obtained by integrating the calibration data with the transition of the panel. The range data is acquired by interpolating the center position of the slit light laser to the calibration coordinates. Experimental results show that the proposed method provides the accuracy of 0.08mm error in depth range of 130mm with the low cost optical system.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.38.4-38
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• 2002

We propose a fast map-matching algorithm based on the length and the slope for the sequence of lines extracted from a laser range finder and a map. After finding two feature set from laser data and a map, the position and heading of the mobile robot can be determined exactly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.938-941
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• 2003

As the application area of range finder initially developed for military purpose has been extended, the necessity of precision measurement for long distance and its miniaturization is being presented. Recently, LRF(Laser Range Finder) is widely used because it shows more accurate results of range finding. However, most of LRFs use laser source which have wavelength ranges harmful to the human eyes. In this study, we developed the LRF using OPO(Optical Parametric Oscillator) which can stretch laser wavelength to safe region and realized more compact one using solid state laser

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.152-159
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• 2007

In this paper, a new design technique on the LRF which is useful for low power laser and a CBDA(Cummulative Binary Detection Algorithm) is proposed. The LD(Laser Diode) and Si-APD(Silicon Avalanche Photo Diode) are used for saving a power. In order to prove the detection range, the Si-APD binary data are accumulated before the range computation and the range finding algorithm. A prototype of the proposed DLRF(Diode Laser Range Finder) system was made and tested. An experimental result shows that the DLRF system have the same detection range using a less power(almost 1/32) than an usual military LRF. The proposed DLRF can be applied to the Unmanned Vehicles, Robot and Future Combat System of a tiny size and a low power LRF.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1423-1426
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• 2005

Map building is the most important thing for the mobile robots navigation. It requires specific vision system such as CCD camera, range finding system, and many other things. Laser range finder has highly collimated beams can be obtained easily, thus achieving lateral resolution. Laser Diode is used for a continuous laser source. The Automatic Current Control Circuit and the Bias-T is used for mix AC signal with DC bias. This signal is used for driving Laser Diode. The main idea of the calculating distance is detecting phase shift between reference signal and detected signal by photo detector. For the signal processing, the Lock-in amplifier system is addressed in this paper. We used a diffused reflected beam to detect phase shift in this system. But this beam is minuteness signal so it can be easily buried in nose. Lock-in amplifier is used to measure the amplitude and phase of signals which are buried in noise.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.415-420
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• 1989

This thesis deals with range finding using one camera and laser pointer. Range finding will be used further recognition of the image, that is, range image which allows further segmentation of the scene. In the first step, camera modeling is performed by camera calibration which executes least square fit. Least square fit uses the method of sigular value decomposition. And perspective transform of camera is obtained. Lastly range finding is performed by triangulation principle. The result of this algorithm are displayed.

• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.69-74
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• 2001

Detection of operation lines in farm works, object recognition and obstacle avoidance are essential pre-requisite technologies for unmanned agricultural machinery. A CCD camera, which has been largely used for these functions, is expensive and has difficulty in real-time signal processing. In this study, a laser range sensor was selected as the guiding vision for unmanned agricultural machinery such as a tractor. To achieve this capability, algorithms for distance measurement, signal filtering, object recognition, and obstacle avoidance were developed. Computer simulations were carried out to evaluate performance of the algorithms. Experiments were also conducted with various materials and shapes, Laser beam lost its intensity for poor reflective materials, resulting in less range value than actual, so a compensation technique was considered to be necessary. Object detection system was fabricated on an agricultural tractor and the performance was evaluated. As test result for obstacle detection and avoidance in field, to detect and avoid obstacle for path finding with guiding system for unmanned agricultural machinery was enable.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.521-525
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• 2011

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.